Another Earth. Date unknown. Felix Geremus. https://www.linkedin.com/in/felix-geremus-97515273/ (AI & Environment Resource Hub; record atlas-9a47429d159b; collection snapshot 2026-09-15).
Classification and context
Included in the original People of Interest collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
This is a directory, not an expert survey, ranking, or inferred affiliation network. Check deferred after source rate limit · checked 2026-09-06. Metadata not yet corroborated. The import date is not the original date added.
This study introduces a new foundation model based on the Prithvi-EO Vision Transformer, pre-trained on Sentinel-3 ocean color data, to enhance marine Earth observation. By fine-tuning on chlorophyll and primary production tasks, the model outperforms traditional baselines, showing that self-trained AI can extract detailed spatial patterns from limited labeled data and improve monitoring of ocean ecosystems and climate processes.
arXiv
Shared topics: Research tools and geospatial methods; Climate and greenhouse gases; Biodiversity and ecosystems
This study presents a new machine learning (Light Gradient Boosting Machine) approach to generate high-resolution, hourly maps of gross primary productivity (GPP) for East Asia (2020–2021). The paper highlights clear diurnal patterns across different land cover types and latitudes, offering valuable insights for ecosystem monitoring and carbon cycle modeling.
Remote Sensing of Environment
Shared topics: Research tools and geospatial methods; Climate and greenhouse gases; Biodiversity and ecosystems
Researchers created a global open-access database of 575 nature-based carbon offset project boundaries to improve transparency and verification, using both automated and manual geospatial methods with high accuracy.
